package com.tanhua.dubbo.api;

import cn.hutool.core.collection.CollUtil;
import com.tanhua.model.mongo.RecommendUser;
import com.tanhua.model.mongo.UserLike;
import com.tanhua.model.vo.PageResult;
import org.apache.dubbo.config.annotation.DubboService;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.data.domain.Sort;
import org.springframework.data.mongodb.core.MongoTemplate;
import org.springframework.data.mongodb.core.aggregation.Aggregation;
import org.springframework.data.mongodb.core.aggregation.AggregationResults;
import org.springframework.data.mongodb.core.aggregation.TypedAggregation;
import org.springframework.data.mongodb.core.query.Criteria;
import org.springframework.data.mongodb.core.query.Query;

import java.util.List;

@DubboService
public class RecommendUserApiImpl implements RecommendUserApi{

    @Autowired
    private MongoTemplate mongoTemplate;

    //查询今日佳人
    @Override
    public RecommendUser queryWithMaxScore(Long toUserId) {
        //1,根据toUserId查询，根据评分score排序，获取第一条
        //构建Criteria
        Criteria criteria = Criteria.where("toUserId").is(toUserId);
        //构建Query对象
        Query query = Query.query(criteria).with(Sort.by(Sort.Order.desc("score")))
                .limit(1);
        //调用mongoTemplate查询
        return mongoTemplate.findOne(query, RecommendUser.class);
    }

    //分页查询
    @Override
    public PageResult queryRecommendUserList(Integer page, Integer pageSize, Long toUserId) {
        //1,构建Criteria对象
        Criteria criteria = Criteria.where("toUserId").is(toUserId);
        //2,构建query对象
        Query query = Query.query(criteria);
        //3,查询总数
        long count = mongoTemplate.count(query, RecommendUser.class);
        //4,查询数据列表
        query.with(Sort.by(Sort.Order.desc("score"))).limit((page - 1) * pageSize).skip(pageSize);
        List<RecommendUser> list = mongoTemplate.find(query, RecommendUser.class);
        return new PageResult(page,pageSize,count,list);
    }

    @Override
    public RecommendUser queryByUserId(Long userId, Long toUserId) {
        Criteria criteria = Criteria.where("toUserId").is(toUserId).and("userId").is(userId);
        Query query = Query.query(criteria);
        RecommendUser recommendUser = mongoTemplate.findOne(query, RecommendUser.class);
        if (recommendUser == null) {
            recommendUser = new RecommendUser();
            recommendUser.setUserId(userId);
            recommendUser.setToUserId(toUserId);
            //构建缘分值
            recommendUser.setScore(95D);
        }
        return recommendUser;
    }

    /**
     * 1,排除喜欢，不喜欢的用户
     * 2,随机展示
     * 3,指定数量
     */
    @Override
    public List<RecommendUser> queryCardsList(Long userId, int counts) {
        //1,查询喜欢不喜欢的用户id
        List<UserLike> likeList = mongoTemplate.find(Query.query(Criteria.where("userId").is(userId)), UserLike.class);
        List<Long> likeUserIds = CollUtil.getFieldValues(likeList, "likeUserId", Long.class);
        //2,构造查询推荐用户的条件
        Criteria criteria = Criteria.where("toUserId").is(userId).and("userId").nin(likeUserIds);
        //3,使用统计函数，随机获取推荐的用户列表
        TypedAggregation<RecommendUser> newAggregation = TypedAggregation.newAggregation(RecommendUser.class,
                Aggregation.match(criteria), //指定查询条件
                Aggregation.sample(counts)
        );
        AggregationResults<RecommendUser> results = mongoTemplate.aggregate(newAggregation, RecommendUser.class);
        //4,构造返回值
        return results.getMappedResults();
    }

}
